Published June 17, 2021 | Version v1.0
Dataset Open

Data and code for the publication "Tracing the horizontal transport of microplastics on rough surfaces"

  • 1. Ecosystem Research Group, Institute of Geography, Faculty of Mathematics and Natural Sciences, University of Cologne, Germany
  • 2. Biofluid Simulation and Modeling – Theorethische Physik VI, University of Bayreuth, Germany
  • 3. Animal Ecology I, BayCEER, University of Bayreuth, Germany

Description

Background

The data set contains images of fluorescent PMMA (Polymethyl methacrylate) particles that are moved by water on rough surfaces in an irrigation experiment. The experiments were done in the laboratory at the Institute of Geography, University of Cologne, Germany, in Septembre 2020. The images were taken with an sCMOS (advanced scientific complementary metal-oxide-semiconductor) high resolution pco.panda 4.2 camera (PCO AG, Kehlheim, Germany).

The data set was analysed in the publication: Laermanns, H., Lehmann, M., Klee, M., Löder, M.G.J., Gekle, S. and Bogner, C., 2021, “Tracing the horizontal transport of microplastics on rough surfaces,” Microplastics and Nanoplastics, https://doi.org/10.1186/s43591-021-00010-2

Additionally to the data, this collection of files contains the Python and R scripts/notebooks used to analyse the images and create graphics for the publication. The code for the simulation of flow patterns can be obtained from the authors upon request.

 

Disclaimer

The data and code are provided as is without any warranty.

Experimental parameters

  • Surface roughness: two levels, fine and course

  • Inclination: 6 levels, 2.5°, 5°, 7.5°, 10°, 12.5° and 15°

  • Irrigation: three levels, 4.8, 7.2 and 10.44 L/h

  • Repetitions: three

More details on the experimental setup are given in the publication.

 

Description of the dataset

The folder images.zip contains the images. They are organized as follows:

  • Feinsand_10_Partikel: images of PMMA particles on the fine surface
  • Grobsand_10_Partikel: images of PMMA particles on the rough surface
    • Both folders contain six subfolders _XX_Grad_Gefaelle, XX being 2_5, 5, 7_5, 10, 12_5, 15. These folders refer to inclinations of 2.5°, 5°, 7.5°, 10°, 12.5° and 15° of the rough surfaces, respectively.

    • every folder _XX_Grad_Gefaelle contains three subfolders Fliessgeschwindigkeit_YY, with YY being 20mlx4, 30mlx4 and 43_5mlx4, the parameters of the peristaltic pump, corresponding to irrigation rates of 4.8, 7.2 or 10.44 L/h, respectively.

    • every folder Fliessgeschwindigkeit_YY contains three subfolders Z_Durchgang with Z being 1, 2 or 3 corresponding to the tree repetitions of the experiment.

  • stained_flow_patterns: images of flow patterns of the fluorescent dye Nile Red (in methanol), an mp4 video and a text file with parameters to produce the video based on the images. The images were produced for the following experimental parameters:
    • Feinsand_2_5_Grad_20_ml: fine surface, inclined by 2.5° and irrigated with 7.2 L/h

    • Grobsand_7_5_Grad_20_ml: coarse surface, inclined by 7.5° and irrigated with 7.2 L/h

The file experimental_data.csv links the concatenated folder names to experimental parameters.

 

Description of the code

The images were first processed in Python to locate the PMMA particles and calculate particle sizes. The Python code is located in the py_scripts.zip folder. It contains the following files:

  • find_XYZ: locates PMMA particles. XYZ stands for different experimental parameters (see above). Scripts containing the string _problems locate PMMA particles for images with possible artefacts (smeared particles, residual light etc.). You need to uncomment the appropriate lines in the files to rerun the code because it was run piece by piece.

  • pickle_to_csv.py: converts pickle files to csv files

  • calculate_sizes.py: calculates the sizes of PMMA particles from the first image of each experiment

  • py_functions_new.py: contains custom functions

Further analysis run in a mixture of R and Pyhton in one working document (R Notebook):

  • Analysis_with_loops.Rmd: tracking of the PMMA particles by PtrakPy version 0.4.2 (Allan et al. 2019). Python 3.8 (Python Software Foundation, https://www.python.org/) was called directly from R using the R package reticulate (https://rstudio.github.io/reticulate/) in RStudio (https://www.rstudio.com/).

  • Analysis_for_paper.Rmd: R code for analysis of tracking, statistical analysis, plotting. We used the R version 4.0.3 (R Core Team 2020).

  • helper_function.R: contains custom R functions for the analysis

 

Results

The file results.zip contains the folders:

  • data: *.pickle files produced by Python containing the trajectories of PMMA particles

  • data_csv: *.pickle files converted to *.csv files

  • figures: figures produced by the code during the analysis, organized in different subfolders

  • RData: large computational results produced and saved during analysis

  • sizes_csv: *.csv files containing PMMA particle sizes and further morphological characteristics; produced during analysis

 

Acknowledgements

The authors thank Julia Horn for support in the laboratory and Florian Steininger for technical assistance.

 

Funding

This project was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Project Number 391977956, SFB 1357, subprojects B04 and B06.

 

References

Allan, Dan, Casper van der Wel, Nathan Keim, Thomas A Caswell, Devin Wieker, Ruben Verweij, Chaz Reid, et al. 2019. Soft-Matter/Trackpy: Trackpy V0.4.2 (version v0.4.2). Zenodo. https://doi.org/10.5281/zenodo.3492186.

Laermanns, Hannes, Moritz Lehmann, Marcel Klee, Martin GJ Löder, Stephan Gekle, and Christina Bogner. 2021. “Tracing the Horizontal Transport of Microplastics on Rough Surfaces.” Microplastics and Nanoplastics. https://doi.org/10.1186/s43591-021-00010-2.

R Core Team. 2020. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

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